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Director, Mobility Analytics, Strategy & Planning

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Uber
Full Time position
Listed on 2026-06-27
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 239000 - 265500 USD Yearly USD 239000.00 265500.00 YEAR
Job Description & How to Apply Below

About the Role

We’re looking for a Director to lead the Customer Advocacy & Solutions’s Mobility engine that helps make and scale decisions. This leader owns the AI-led analytical backbone, the strategic narrative, and the operating cadence that keeps a multi-billion-dollar business moving in the same direction.

You're joining at an inflection point. We’re driving a transformation in our customer experience while growing at a rapid clip. The foundationals KPIs are changing and the very metrics that define "good" will shift underneath us as we move to an AI‑first world s leader keeps the numbers trustworthy and comparable through that change, so the org can always tell real signals from a moving baseline.

We want a builder: someone who is AI‑first by instinct
, treats analytics, insights & planning as a scaled platform rather than a service desk, and can turn messy operational reality into clear, defensible strategy that executives act on. You’ll partner closely with Product, Engineering, Operations, and Finance, and you’ll be a trusted thought partner to senior leadership.

If you get energy from standing up systems that outlast any single project and you’d rather teach a model to answer a question than answer it manually a thousand times this role is for you.

This role is based in San Francisco and co‑located with the leadership team. We believe the strategy, analytics, and planning function does its best work in close partnership — high‑bandwidth, in the room, building together.

What You’ll Do
  • Lead a multidisciplinary team spanning Analytics, Strategy, Planning, and Program Management, setting a high bar for rigor, speed, and clarity.
  • Set the data integrity bar and enforce it. Establish data quality standards, lineage, SLAs, and alerting across Mobility's core datasets, so corruption and drift get caught before they hit eligibility, payouts, or decisions not after.
  • Step‑change time‑to‑root‑cause. Build AI‑assisted investigation automated anomaly detection, root‑cause triage, and self‑serve diagnostics that turns multi‑day investigations into same‑day (or same‑hour) answers, and makes "why did this move?" a question the org can answer itself.
  • Build scaled analytics platforms
    , not one‑off reports. Design the data products, self‑serve tooling, and AI‑assisted workflows that let the broader org answer its own questions and move faster.
  • Embed AI into how the team works. Champion an AI‑first operating model using LLMs, agentic systems, and automation to compress cycle time on analysis, planning, and reporting, to detect and explain anomalies before they become escalations, and to surface insight that wouldn’t scale through human effort alone.
  • Own the strategic narrative for Mobility
    : translate data into a point of view, frame the tradeoffs for executives, and drive alignment on where we invest and why.
  • Run the planning rhythm. Lead annual and quarterly planning, goal‑setting, and the operating cadence that connects strategy to execution and holds the org accountable to outcomes.
  • Drive cross‑functional programs end to end — defining scope, sequencing the work, unblocking teams, and landing results across Product, Engineering, and Ops.
  • Be a force multiplier for leadership
    , surfacing the signals that matter, pressure‑testing decisions, and making sure the team is solving the right problems.
What Good Looks Like

By the end of the first year, this leader should have moved the org to a place where:

  • Investigations that used to take days take hours, and the path from "something's off" to "here’s why" is largely self‑serve in that time horizon.
  • Leaders trust the numbers enough to act on them without re‑checking because integrity, lineage, and monitoring are built in, not bolted on.
  • AI and automation carry a meaningful share of the analysis, reporting, and anomaly detection proactively that used to consume the team’s time.
  • Strategy, planning, and execution run on one connected cadence, with a clear, defensible point of view on where Mobility invests and why.
Core Skills We’re Looking For
  • Expertise in Data, Analytics & AI – Strong understanding of enterprise data platforms, analytics ecosystems, AI/ML workflows, and modern data…
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